Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimi...

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Main Authors: Yong Peng, Yali Zhang, Dennis Z. Yu, Yijuan Luo
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Mathematics
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Online Access:https://www.mdpi.com/2227-7390/12/22/3559
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author Yong Peng
Yali Zhang
Dennis Z. Yu
Yijuan Luo
author_facet Yong Peng
Yali Zhang
Dennis Z. Yu
Yijuan Luo
author_sort Yong Peng
collection DOAJ
description The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.
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spelling doaj-art-eb3e9c7860ce4d94a6ba5f5b7cb8c4872025-08-20T02:04:58ZengMDPI AGMathematics2227-73902024-11-011222355910.3390/math12223559Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food WasteYong Peng0Yali Zhang1Dennis Z. Yu2Yijuan Luo3School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, ChinaThe David D. Reh School of Business, Clarkson University, Potsdam, NY 13699, USAPort and Shipping Maritime Affairs Center, Qijiang District, Chongqing 401420, ChinaThe cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.https://www.mdpi.com/2227-7390/12/22/3559multimodal cold chainmultiobjective optimizationcarbon emissionsfood waste
spellingShingle Yong Peng
Yali Zhang
Dennis Z. Yu
Yijuan Luo
Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste
Mathematics
multimodal cold chain
multiobjective optimization
carbon emissions
food waste
title Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste
title_full Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste
title_fullStr Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste
title_full_unstemmed Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste
title_short Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste
title_sort multiobjective route optimization for multimodal cold chain networks considering carbon emissions and food waste
topic multimodal cold chain
multiobjective optimization
carbon emissions
food waste
url https://www.mdpi.com/2227-7390/12/22/3559
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AT yalizhang multiobjectiverouteoptimizationformultimodalcoldchainnetworksconsideringcarbonemissionsandfoodwaste
AT denniszyu multiobjectiverouteoptimizationformultimodalcoldchainnetworksconsideringcarbonemissionsandfoodwaste
AT yijuanluo multiobjectiverouteoptimizationformultimodalcoldchainnetworksconsideringcarbonemissionsandfoodwaste